%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2016/07.18.12.43
%2 sid.inpe.br/sibgrapi/2016/07.18.12.43.05
%@doi 10.1109/SIBGRAPI.2016.018
%T Personalized visual simulation and objective validation of low-order aberrations of the human eye
%D 2016
%A Krueger, Matheus Luan,
%A Oliveira Neto, Manuel Menezes de,
%A Kronbauer, Airton Leite,
%@affiliation UFRGS
%@affiliation UFRGS
%@affiliation CORS
%E Aliaga, Daniel G.,
%E Davis, Larry S.,
%E Farias, Ricardo C.,
%E Fernandes, Leandro A. F.,
%E Gibson, Stuart J.,
%E Giraldi, Gilson A.,
%E Gois, João Paulo,
%E Maciel, Anderson,
%E Menotti, David,
%E Miranda, Paulo A. V.,
%E Musse, Soraia,
%E Namikawa, Laercio,
%E Pamplona, Mauricio,
%E Papa, João Paulo,
%E Santos, Jefersson dos,
%E Schwartz, William Robson,
%E Thomaz, Carlos E.,
%B Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)
%C São José dos Campos, SP, Brazil
%8 4-7 Oct. 2016
%I IEEE Computer Society´s Conference Publishing Services
%J Los Alamitos
%S Proceedings
%K personalized visual simulation, low-order aberrations, fourier optics, PSF.
%X We present a practical approach for personalized simulation and objective validation of the effects of low-order aberrations (i.e., myopia, hyperopia and astigmatism) on optical systems, such as the human eye. We characterize the optical aberrations using a wavefront aberration function derived from one's eyeglasses or contact lenses prescription data, expressed in terms of Zernike polynomials. Given the prescription data, a target image at known distance from the subject, and a specified pupil size, the simulation efficiently computes the corresponding aberrated view. We validate the quality of our simulations using ground truth data captured by a camera with the same kind of aberrations. For validation, we use three objective metrics: structural similarity (SSIM), peak signal-to-noise ratio (PSNR), and absolute pixelwise differences (AD) between the simulated images and the ones captured by the camera with induced aberrations. Our results achieved a SSIM mean value of 0.93 (minimum of 0.91) and a PSNR mean value of 35.50 dB (minimum of 29.50 dB), showing that they are structurally similar and virtually indistinguishable from the ground truth images captured by the camera.
%@language en
%3 PID4363883.pdf